Financial econometrics, mathematics, statistics, and financial technology: an overall view

Lee, Cheng Few

doi:10.1007/s11156-020-00883-z

Cited by 12 publications

(2 citation statements)

References 144 publications

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“…By combining knowledge of financial intelligence and financial mathematics, one can make better financial decisions, manage finances more effectively, and achieve short-term and long-term financial goals (Lee, 2020).…”

Section: Resultsmentioning

confidence: 99%

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Developing Financial Intelligence With Financial Mathematics

Gunawan,

Jannah

2024

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Financial intelligence is an individual's ability to understand, manage, and optimize the management of personal finances. Financial mathematics is becoming an important tool in developing financial intelligence. In this research using literature study method this method involves the search and collection of information from related literature sources. Through financial mathematics, one can calculate the future value of an investment, estimate the return on an investment, calculate annuity payments, understand the concept of time value of money, and analyze investment risk. The application of financial mathematics in financial intelligence provides an advantage in taking better financial decisions and managing finances effectively. By utilizing financial mathematics, one can improve their understanding of Finance, make effective financial planning, and take better financial decisions.

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Section: Resultsmentioning

confidence: 99%

“…Developing financial intelligence through financial mathematics is also reflected in the increasingly complex and dynamic global environment (Lee, 2020). Given the continuously changing and rapidly developing world, the ability to understand and apply financial mathematics concepts provides an advantage in making financial decisions.…”

Section: Introductionmentioning

confidence: 99%

Developing Financial Intelligence With Financial Mathematics

Gunawan,

Jannah

2024

Orics

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Alternative Machine Learning Methods for Credit Card Default Forecasting*

Lee¹,

Chang

Kao

et al. 2023

Essentials of Excel VBA, Python, and R

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Deep learning in economics: a systematic and critical review

2023

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From the perspective of historical review, the methodology of economics develops from qualitative to quantitative, from a small sampling of data to a vast amount of data. Because of the superiority in learning inherent law and representative level, deep learning models assist in realizing intelligent decision-making in economics. After presenting some statistical results of relevant researches, this paper systematically investigates deep learning in economics, including a survey of frequently-used deep learning models in economics, several applications of deep learning models used in economics. Then, some critical reviews of deep learning in economics are provided, including models and applications, why and how to implement deep learning in economics, research gap and future challenges, respectively. It is obvious that several deep learning models and their variants have been widely applied in different subfields of economics, e.g., financial economics, macroeconomics and monetary economics, agricultural and natural resource economics, industrial organization, urban, rural, regional, real estate and transportation economics, health, education and welfare, business administration and microeconomics, etc. We are very confident that decision-making in economics will be more intelligent with the development of deep learning, because the research of deep learning in economics has become a hot and important topic recently.

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Financial econometrics, mathematics, statistics, and financial technology: an overall view

Cited by 12 publications

References 144 publications

Developing Financial Intelligence With Financial Mathematics

Developing Financial Intelligence With Financial Mathematics

Alternative Machine Learning Methods for Credit Card Default Forecasting*

Deep learning in economics: a systematic and critical review

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